Update utils_mask.py

utils_mask.py

@@ -77,6 +77,7 @@ def get_mask_location(model_type, category, model_parse: Image.Image, keypoint:
     arms_left = (parse_array == 14).astype(np.float32)
     arms_right = (parse_array == 15).astype(np.float32)
 
+   
     if category == 'dresses':
         # Initial dress mask for the upper body
         parse_mask_upper = np.logical_or((parse_array == label_map["upper_clothes"]), (parse_array == label_map["dress"])).astype(np.float32)
@@ -91,10 +92,17 @@ def get_mask_location(model_type, category, model_parse: Image.Image, keypoint:
                                                 parse_array == label_map["right_leg"])).astype(np.float32)
 
         # Dilate the leg mask to ensure coverage and fill gaps
-        parse_mask_legs = cv2.dilate(parse_mask_legs.astype(np.uint8), np.ones((6, 6), np.uint8), iterations=6)
+        parse_mask_legs_dilated = cv2.dilate(parse_mask_legs.astype(np.uint8), np.ones((6, 6), np.uint8), iterations=6)
+
+        # Combine the upper body mask with the dilated leg mask
+        parse_mask_total = np.maximum(parse_mask_upper, parse_mask_legs_dilated)
+
+        # Apply further processing as needed (e.g., additional masks or refinements)
+
+        parse_mask = np.logical_and(parser_mask_changeable, np.logical_not(parse_mask_total))
+
+    
 
-        # Combine the upper body mask with the leg mask
-        parse_mask = np.maximum(parse_mask_upper, parse_mask_legs)
 
 
     elif category == 'upper_body':
@@ -176,3 +184,5 @@ def get_mask_location(model_type, category, model_parse: Image.Image, keypoint:
     mask_gray = Image.fromarray(inpaint_mask.astype(np.uint8) * 127)
 
     return mask, mask_gray
+
+